Maximilian O. Besenhard

Thinking continuously: a microreactor for the production and scale-up of biodegradable, self-assembled nanoparticles

Scale-up of nanoparticle batch productions continues to be a major challenge in the pharmaceutical nanotechnology. Continuously operating microreactors have great potential to circumvent the scale-up difficulties. In this work a passive microreactor was used for the first time for the electrostatic self-assembly of biodegradable, mucoadhesive thiomer–protamine nanoparticles for drug delivery. The influence of three different parameters (the overall flow rate, the educt mass ratio and the molecular weight of the thiomer) on the particle characteristics was tested for the microreactor production and compared to the results of a successful 1 ml-batch reaction. As the flow rate increased (2, 5, 9, 16 ml min−1), the particle sizes and the polydispersity indexes decreased. In addition, the protamine : 5 kDa thiomer binding ratio and hence the zeta potential, as a measure of the suspensions stability, increased to >+40 mV due to better mixing during the microreactor production at a flow rate of 16 ml min−1. Producing nanoparticles from different mass ratios of 5 kDa thiomer : protamine (1 : 1, 1 : 3, 1 : 5) in the microreactor at this flow rate resulted in smaller particles with more distinct zeta potentials than those prepared by the 1 ml-batch reaction. Using a higher molecular weight thiomer (30 kDa) for the microreactor production at a flow rate of 16 ml min−1 led to slightly increased mean particle sizes (125.0 nm) compared to those produced by the 1 ml-batch reaction (102.9 nm). However, there was still a decrease in the width of the particle size distributions. In addition to the experimental work, a numerical model based on the population balance equation was developed. The results presented in this paper are in agreement with the experimental findings, especially with regard to the trends of decreased particle size and polydispersity with the increasing flow rate. The model results confirm that mixing effects to a great extent determine the particle size distribution of the resulting nanoparticles and show that spatial inhomogeneity of the mixing process must be taken into account. The unprecedented use of a passive microreactor for the production of biodegradable thiomer–protamine nanoparticles by electrostatic self-assembly was a success. Due to the reactors continuous way of operation, not only were the scale-up problems of batch reactions overcome, but particle characteristics were also improved because of a better mixing effect.

Crystal Engineering in Continuous Plug-Flow Crystallizers

Size, shape, and polymorphic form are the critical attributes of crystalline particles and represent the major focus of today’s crystallization process design. This work demonstrates how crystal properties can be tuned efficiently in solution via a tubular crystallizer that facilitates rapid temperature cycling. Controlled crystal growth, dissolution, and secondary nucleation allow a precise control of the crystal size and shape distribution, as well as polymorphic composition. Tubular crystallizers utilizing segmented flow such as the one presented in our work can provide plug flow characteristics, fast heating and cooling, allowing for rapid changes of the supersaturation. This makes them superior for crystal engineering over common crystallizers. Characterization of particle transport, however, revealed that careful selection of process parameters, such as tubing diameter, flow rates, solvents, etc., is crucial to achieve the full benefits of such reactors.

A multivariate process monitoring strategy and control concept for a small-scale fermenter in a PAT environment

This work describes a multivariate monitoring and control concept for bioprocesses based on historical process data. The concept is demonstrated for a Saccharomyces Cerevisiae (baker’s yeast) fermentation process executed in a small-scale bioreactor, which is equipped with common probes to analyze the broth and off-gases. The data of “in-control” fermentation processes were evaluated by means of a principal component analysis to define confidence limits for subsequent fermentations. A violation of these limits indicated that a process had to be classified as “out-of-control”. Fault diagnosis was provided by the components of the squared prediction error, which can also be used to determine the appropriate counteractions, e.g. via an expert system control strategy as described in this study. The sensitivity of fault diagnosis was demonstrated via various erroneous runs. The duration of bioprocesses can vary distinctly, which complicates the definition of time dependent control limits. Therefore, this study utilizes a three-component partial least squares regression model to quantify the current batch maturity during the process. This maturity is then used to reference current data to the appropriate historical data and the assigned control limits.

Crystal shape modification via cycles of growth and dissolution in a tubular crystallizer

Besides size and polymorphic form, crystal shape takes a central role in engineering advanced solid materials for the pharmaceutical and chemical industries. This work demonstrates how multiple cycles of growth and dissolution can manipulate the habit of an acetylsalicylic acid crystal population. Considerable changes of the crystal habit could be achieved within minutes due to rapid cycling, i.e., up to 25 cycles within <10 min. The required fast heating and cooling rates were facilitated using a tubular reactor design allowing for superior temperature control. The face-specific interactions between solvent and the crystals’ surface result in face-specific growth and dissolution rates and hence alterations of the final shape of the crystals in solution. Accurate quantification of the crystal shapes was essential for this work, but is everything except simple. A commercial size and shape analyzer had to be adapted to achieve the required accuracy. Online size, and most important shape, analysis was achieved using an automated microscope equipped with a flow-through cell, in combination with a dedicated image analysis routine for particle tracking and shape analysis. Due to the implementation of this analyzer, capable of obtaining statistics on the crystals’ shape while still in solution (no sampling and manipulation required), the dynamic behavior of the size shape distribution could be studied. This enabled a detailed analysis of the solvent’s effect on the change in crystal habit.